Audience responsiveness analytics index for television advertising

ABSTRACT

A system and methods are disclosed for creating and using an audience-responsiveness analytics index for television advertising, in particular, advertising for connected television viewing. The audience-responsiveness analytics index may be configured to provide data obtained or acquired by measuring audience responsiveness to video advertising placed in streaming content viewed over connected televisions. The audience-responsiveness analytics index may be a graph used to optimize advertising with households assigned scores for multiple categories of advertising.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority under 35 USC § 119(e) to U.S.Provisional Application No. 63/169,110, entitled “AudienceResponsiveness Analytics Index for Television Advertising” filed on Mar.31, 2021, the entirety of which application is herein incorporated byreference.

BACKGROUND 1. Field of the Invention

The present invention relates to paid content or advertisement (“ad”)placement (e.g., video) for connected television viewing over theinternet. More particularly, the present invention relates to a systemand method for creating and using an audience-responsiveness analyticsindex for paid content or advertising (e.g., video) for display instreaming content viewed in a connected television (“CTV”) orover-the-top (“OTT”) environment.

2. Description of the Related Art

With the popularity and use of the Internet for streaming content,connected television or “CTV” or over-the-top (“OTT”) deliverymechanisms use has grown dramatically in recent years. A CTV is a devicethat can connect to a TV or a smart TV that facilitates the delivery ofstreaming video content over the internet. A smart TV is a televisionwith a built-in internet connection and media platform. No additionalequipment is required to stream videos. Instead, videos are most oftenstreamed via apps that are downloaded. Other connected devices thatconnect directly to a traditional television (not a smart television)and the internet and enable apps that are downloaded for viewing videosinclude Xbox, PlayStation, Roku, Amazon Figure TV, Apple TV, Chromecast,and more. Gaming consoles act as the connected device that provideaccess to apps from their app stores. These are referred to as “OTT”(Over-the-Top) devices. With this growth there has been an equallydramatic growth and migration to CTV advertising. For consumers, “CTV”is a different way to watch TV across multiple types of screens with nocable or satellite subscription required. For advertisers, it's aninnovative way to reach a new and unique audience. Today's viewers areincreasingly turning to diverse viewing options that don't necessarilyinvolve a traditional television. They are watching smart TVs, laptops,smartphones, game consoles (Nintendo switch, Xbox, PlayStation) andother connected devices such as Amazon Fire, Roku, and Apple TV.However, programmatic advertising presents a complex eco-systeminvolving a complicated interplay between several entities, includingcontent providers, advertisers (both informed and uninformed), and usersor viewers who browse the internet to view all types of streamed contentavailable via websites that are of interest to them.

With connected TV advertising, advertisers can typically reachtelevision viewers that advertisers cannot reach without traditional TVcommercials. Superior targeting capabilities involve connectedtelevision audience targeting, by which companies can be sure thatmarketing dollars are going towards the most valuable and targetedviewers. In this industry, programmatic platforms allow measurement ofthe results of connected TV campaigns with both digital and traditionalmetrics, including video completion rates. Growing audience targetsmillennials and the growing population who do not use cable TV, alsoknown as “cord cutters.”

Connected TV advertising is becoming a powerful open platform thatcaters directly to a variety of new applications and services to homes,mainly for the young, middle-aged, and older adult population. Such arobust, tech-savvy audience represents incredible marketingopportunities with brands continuously seeking metrics to targetspecific advertising to viewers. Similar to other video advertisements,Connected TV advertisements may be pre-roll or mid-roll. Pre-roll adsare those shown before content and mid-roll ads are those shown in themiddle of content. Considering most ads on Smart TVs are un-skippableand users are highly engaged (having carefully selected content they aremost interested in viewing), CTV advertisements are extremely effective.Moreover, CTV ads are far more measurable than traditional TVadvertising. With access to data, advertisers can quickly adjust theirstrategy based on what has or hasn't been working for their campaigns.

There is a need in the industry for continuous improvements to providinganalytics data to create better advertising experiences for viewers.

SUMMARY

The present technology provides digital advertising functionalities fortelevision in a buying and attribution platform that facilitatesself-serve solutions that combine fully optimized media buying withcomprehensive measurement and attribution. The present inventionintroduces a demand-side platform that provides performance-basedadvertising by creating an analytics index for gauging audienceresponsiveness to connected television (CTV) advertising.

The demand-side platform is a dynamic platform that creates an analyticsindex. It comprises one or more computing architectures with processorsthat are distributed across networks to create a programmaticadvertising environment. The analytics index for measuring audienceresponsiveness comprises a plurality of engines that are configured toperform functionalities to create the index. The analytics index iscreated by using the following criteria. In some implementations, ahousehold (“HH”) CTV/OTT responsiveness index is created by configuringengines to collect data on households that are identified as “Exposedand Converting,” which data is written to an operating platform'shousehold-responsiveness graph. It should be recognized that “Exposed”refers to a household that has access to connected television andcapability to view CTV or OTT advertising. In accordance with someaspects of the invention, as the “Exposed” household continues to beexposed to future or more CTV/OTT ads, increments are added to the“exposed vs outcome” index with each instance of viewing or display.

In some embodiments, values are determined according to the number,length of time from advertisement exposure to action, and category ofconversions completed and assigned to the households or homes.

In some embodiments, the household (“HH”) advertising responsivenessindex measures households exposed to advertising or ads, by advertisingcategory (CPG, Auto, Travel, commerce, etc.). The advertisingresponsiveness measure households that have a) seen the CTV/OTT ad andresponded to the CTV/OTT ad, usually via a “second screen response”mechanism (seeing a CTV/OTT ad and responding by using their cell phoneto go to the advertiser website or other example provided below). Insome embodiments, the index also measures the impact of frequency onconversions. For example, the response rate after seeing one ID is “X,”responsiveness after seeking two ads is “Y,” etc. Another measurement istime from CTV/OTT to action. For example, how much time did it take fora house (or group of houses) to respond to an ad after seeing the ad. Insome instances, measurements are taken by advertisement vertical, and byprofile of the household (demo, etc.).

In some embodiments, the index measures advertising responsiveness byhousehold frequency, including cross channel (e.g., CTV addelivery+display+OTT+++). An index created at the household (“HH”) levelthat dictates the optimal frequency and combination of ad formats insupport of CTV/OTT ad delivery to drive ad responsiveness.

In some embodiments, the index measures second-screen audience responseto television advertising. The second screen response encompassesinstances when users/viewers/audience are exposed to a CTV/OTTadvertising and then undertake one of the following actions. It shouldbe recognized that the actions described here are provided as examples,but may not limited to these specific examples. For example, pick up acell phone and go directly or indirectly to the advertiser's site, pickup a laptop computer and go directly to the CTV advertiser's site, pickup a tablet and navigate directly or indirectly to the CTV advertiser'ssite, go to the desktop computer and navigate directly or indirectly tothe CTV advertiser's site, pick up a cell phone and engage with a QuickResponse (“QR”) code in the CTV ad, taking them to the advertiser'soffer page; and pick up the cell phone and dial a phone number to engagewith the CTV advertiser.

The system and methods disclosed below may be advantageous in a numberof respects. They provide a CTV advertising audience responsivenessindex for use in CTV advertising.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example, and not by wayof limitation in the figures of the accompanying drawings in which likereference numerals are used to refer to the same or similar elements.

FIG. 1A is high-level block diagram, illustrating an example system andexample CTV/OTT advertising environment in which the CTV/OTT advertisingaudience responsiveness analytics index created in accordance with thepresent invention operates according to some implementations of thepresent technology.

FIG. 1B is a high-level diagram of the architecture and event flow.

FIG. 2 is a high-level block diagram, illustrating an example CTV/OTTadvertising audience responsiveness analytics index configured tooperate with a market floor engine and auction event store operating afloor auction for CTV/OTT ad placement.

FIG. 3 is a block diagram, illustrating a flow chart of the approach tocreating and using the CTV/OTT advertising audience responsivenessanalytics index.

FIG. 4 illustrates an example index.

DETAILED DESCRIPTION

The systems and methods of this technology are configured to beimplemented in a demand-side platform (“DSP”) for advertising forconnected television (“CTV”) or over-the-top (“OTT”) deliverymechanisms. A typical demand-side platform integrates with multiplesources such as data management platforms (“DMPs”), ad exchanges, supplysources etc., in an infrastructure that provides secure, elastic,compute capacity in the “cloud” that comprises computers from VirtualMachines and Bare Metal servers to high performance computing (“HPC”),graphics processing units (“GPU”), container orchestration andmanagement etc. A demand-side platform is typically integrated in threephases, the first, involving research and set up. The second phase isthe development stage and the final phase is testing the integration.Demand-side platforms typically support cross-channel platforms andintegrate with all the main ad exchanges. The bidding process is one ofthe key features of a demand-side platform. This is performed by acomponent called “bidder” which is responsible for placing bids oninventory during real-time bidding auctions. Usually, multiple bidderswill be there to manage all real-time demands simultaneously. An AdServer is an essential tool for creative management and for storing anad creative and displaying to a user/viewer when required. Some DSPshave their own ad servers while others may connect to external adservers depending on the architecture. A Campaign tracker helps torecord the data regarding the performance of a particular campaign. Thedata includes clicks, impressions and spends. Once the data is recorded,it will be transferred to the reporting dashboard. The campaign trackerhelps the user/viewer to determine the performance of a particularcampaign. A reporting database stores all the data received from thecampaign tracker. Users/viewers can generate reports by making use ofthis information. User/viewer data is an important part of the DSP,which helps in processing and storing important information about theuser/viewer/audience. User/viewer data may include information regardingbuying habits, interests, age groups, demographic details etc. Marketerscan make use of this information to improve the effectiveness of theircampaigns and bring in better results. A user interface is the dashboardwhere the marketers work on creating, managing and optimizing theircampaigns. Ads in DSPs are sold in a few ways, depending on the DSP.DSPs specifically built for performance campaigns such as app-installs,charge a fee based on CPI (Cost per Install) or CPV (Cost per View) forvideo advertising campaigns. Prices of ad impressions in DSPs aredetermined by a real-time bidding (RTB) process, that takes place withinmilliseconds, as a user loads content or interacts with an app.

DSPs are unique as they offer the same capabilities as what ad networksused to provide, with an addition to a suite of audience targetingoptions. The advantage of DSPs over ad networks is that they provideadvertisers with the ability to do real-time bidding on ads, serve adsto a multitude of platforms, track and optimize—all under a singleinterface. Some targeting options offered by a DSP include—demographictargeting (Targets based on demographic features such as age (or agegroup), job title, gender, education etc.), device targeting (showsviewers ads on specific devices to improve the personalization),re-targeting (targeting existing customers) and so on. DSPs are alsoused for retargeting campaigns. This is possible because they are ableto manage large volumes of ad inventories and recognize ad requests withan ideal target audience, targeted by the advertiser. The DSP inaccordance with the present invention offers a self-serve platform,which is an excellent way to manage ad campaigns. This offers targeting,bidding, budgeting and optimizing of ad campaigns. A DSP can integratewith a data management platform (DMP) that stores audience data, usuallycoming from multiple sources. It allows advertisers to create targetaudiences for their campaign based on 1st party and 3rd party audiencedata. A DMP acts as a single platform that consolidates online andoffline data from various advertisers, creating demographics, behavioraland affinity segments which are then used as targeting options indigital advertising. Performance data from live campaigns are then fedback into the DMP, improving the accuracy of the data. DMPs allowadvertisers to reach their specific target markets while reducingwastage in advertising. A DSP provides global reach and effectivetargeting. Through the present DSP, advertisers can connect to differentsegments of audiences by applying various targeting criteria.

Some portions of the detailed descriptions that follow are presented interms of algorithms and symbolic representations of operations on databits within a computer memory. These algorithmic descriptions andrepresentations are the means used by those knowledgeable in the dataprocessing arts to most effectively convey the substance of their workto others in the art. An algorithm is here, and generally, conceived tobe a self consistent sequence of steps leading to a desired result. Thesteps are those requiring physical manipulations of physical quantities.Usually, though not necessarily, these quantities take the form ofelectrical or magnetic signals capable of being stored, transferred,combined, compared, and otherwise manipulated. It has proven convenientat times, principally for reasons of common usage, to refer to thesesignals as bits, values, elements, symbols, characters, terms, numbersor the like.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise, as apparent from the followingdiscussion, it is appreciated that throughout the description,discussions utilizing terms such as “processing” or “computing” or“calculating” or “determining” or “displaying” or the like, referactions and processes of a computer system, or similar electroniccomputing device, that manipulates and transforms data represented asphysical (electronic) quantities within the computer system's registersand memories into other data similarly represented as physicalquantities within the computer system memories or registers or othersuch information storage, transmission or display devices.

The present technology also relates to an apparatus for performing theoperations described. Parts of this apparatus may be speciallyconstructed for the required purposes, or it may comprisegeneral-purpose computing elements that are selectively activated orreconfigured by a computer program stored in the computer to operate thefunctionalities described in this application. Such a computer programmay be stored in a computer readable storage medium, such as, but notlimited to, any type of disk including floppy disks, optical disks,CD-ROMs, and magnetic disks, read-only memories (ROMs), random accessmemories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, flashmemories including USB keys with non-volatile memory or any type ofmedia suitable for storing electronic instructions, each coupled to acomputer system bus.

Portions of the present technology may take the form of an entirelyhardware embodiment, an entirely software embodiment or animplementation containing both hardware and software elements. In someimplementations, this technology is implemented in software, whichincludes but is not limited to, firmware, resident software, microcode,etc.

Furthermore, this technology may take the form of a computer programproduct accessible from a computer-usable or computer-readable mediumproviding program code for use by or in connection with a computer orany instruction execution system. For the purposes of this description,a computer-usable or computer readable medium can be any apparatus thatcan contain, store, communicate, propagate, or transport the program foruse by or in connection with the instruction execution system,apparatus, or device.

A data processing system suitable for storing and/or executing programcode will include at least one processor coupled directly or indirectlyto memory elements through a system bus. The memory elements can includelocal memory employed during actual execution of the program code, bulkstorage, and cache memories which provide temporary storage of at leastsome program code in order to reduce the number of times code must beretrieved from bulk storage during execution.

Input/output or I/O devices (including but not limited to, keyboards,displays, pointing devices, etc.) can be coupled to the system eitherdirectly or through intervening I/O controllers.

Network adapters may also be coupled to the system to enable the dataprocessing system to become coupled to other data processing systems orremote printers or storage devices through intervening private or publicnetworks. Modems, cable modem, and Ethernet cards are just a few of thecurrently available types of network adapters.

Finally, the algorithms and displays presented here are not inherentlyrelated to any particular computer or other apparatus. Variousgeneral-purpose systems may be used in combination with programs inaccordance with the teachings herein, or it may prove convenient toconstruct more specialized apparatuses to perform certain requiredmethod steps. The required structure for a variety of these systems willappear from the description below. In addition, the present invention isnot described with reference to any particular programming language. Itwill be appreciated that a variety of programming languages, forexample, high level programming languages such as “C,” “Java,” or“Pascal,” or other may be used to implement the teachings of thetechnology as described herein. The computers may be speciallyprogrammed, and be configured with special purpose hardware. Eachcomputer may have a single processor, a multiprocessor or may comprisemultiple computers, each of which may include a single processor or amultiprocessor, operably connected over a computer network. Eachcomputer may be controlled by one of a variety of operating systemsincluding Microsoft Windows, Macintosh, Linux, Unix, or a Java-basedoperating system, to name a few.

Each computer in the system may include one or more input and output(I/O) unit, a memory system, and one or more processing units. Theinput-output (“I/O”) units of each computer may be connected to variousinput/output devices, such as a mouse, keyboard, video card (videomonitor), sound card (with speakers), network card and printer. Thememory system in a typical general purpose computer system usuallyincludes a computer readable and writeable nonvolatile recording medium,of which a magnetic disk, a flash memory and tape are examples. Thememory system operably holds the operating system, utilities, andapplication programs. It should also be understood the invention is notlimited to the particular input devices, output devices, or memorysystems used in combination with the computer system or to thosedescribed herein. Nor should the invention be limited to any particularcomputer platform, processor, or high-level programming language.

System Architecture Overview

FIG. 1 illustrates a block diagram of a CTV/OTT audience responsivenessanalytics index system in a demand-side platform 101 illustrated in aCTV digital advertisement (“ad”) placement environment 100 in which thedisclosed implementation of the CTV audience responsiveness analyticsindex system is operable. The environment 101 includes: an onlineadvertiser server or website 102 (representing one or more onlineadvertisers), an online content server or website 104 (representing oneor more online content providers), a network 106, and a real-timebidding (“RTB”) market platform 108. The online advertiser server 102may be a computing system (of one or more computers or processors,either linked or distributed) that submits bids to the RTB marketplatform 108 to purchase content-provider inventory and have advertiseradvertisements shown in the CTV environment. The advertiser server 102is illustrated as coupled to the RTB market platform via signal line 112and the content server is illustrated as coupled to the RTB marketplatform via line 114. The content server 104 may be a computing systemthat maintains content for televising that attracts viewers and containsplaceholders for ads (from the ad inventory) that are submitted to theRTB market, for sale to advertisers. The content server 104 has accessto data provided by the CTV audience responsiveness analytics index,either directly (not expressly illustrated in FIG. 1 ) or otherwise. TheRTB 108 may be a computing system that provides a real-time biddingmarket that allows advertisers to bid on provider inventory inreal-time. While only a single advertiser server 102, a single contentserver 104 and a single network 106 are shown in FIG. 1 , it should berecognized that there may be thousands or even millions of advertiserservers 102, content servers 104, or networks 106 that integrate in aprogrammatic advertising environment. FIG. 1 is merely provided as oneexample illustration of the systems 102, 104, and 106, which present theenvironment in which the present technology may be implemented.

The advertiser server 102 is coupled by signal line 112 forcommunication with the real-time bidding market 108. Although notexplicitly shown in FIG. 1 , it should be recognized that any and allthe signal lines illustrated in FIG. 1 may route, via the network 106,as illustrated in FIG. 1 . The advertiser 102 is coupled to thereal-time bidding market 108 to send bids on impressions, and alsoprovides advertisement content, advertising target information, price,or any other information related to the impression or necessary to servethe ad on streaming content. The RTB market platform 108 is a real-timebidding market, which allows advertisers to bid on inventory inreal-time.

The content site 104 is a computing device for providing any type ofvideo content for viewing as streamed content on a household or relateddevice. The signal line 114 provides information to the RTB about whichimpressions on the content site are available for the RTB market. Acontrol line 109 from 104 to 106 indicates content provision from theonline content servers.

The network 106 is a conventional type, wired or wireless, and may haveany number of configurations such as a star configuration, token ringconfiguration or other configurations known to those skilled in the art.Furthermore, the network 106 may comprise a local area network (LAN), awide area network (WAN) (e.g., the Internet), and/or any otherinterconnected data path across which multiple devices may communicate.In yet another embodiment, the network 106 may be a peer-to-peernetwork. The network 106 may also be coupled to or includes portions ofa telecommunications network for sending data in a variety of differentcommunication protocols. In yet another embodiment, the network 106includes Bluetooth communication networks or a cellular communicationsnetwork for sending and receiving data such as via short messagingservice (SMS), multimedia messaging service (MMS), hypertext transferprotocol (HTTP), direct data connection, WAP, email, etc.

The RTB market platform 108 is coupled by signal line 118 to anadvertisement server 110, which serves ads, for example video ads. Thead server 110 is software that receives requests for ad units, submits,and then fulfills those requests with content. The advertisement server110 is coupled to the network 106 for communication and interaction withonline advertisers 102 and the content site 104. A viewer (audience) 125who is viewing streamed content is a potential consumer of ads. Theremay be any number of viewers (audience) 125 a, 125 b, through 125 n, whoare coupled via the network 106 to online sites 104 from which contentmay be streamed. For example, when a viewer in the audience (125 a-125n) downloads content for viewing that is supplied by an online contentsite 104, requests are sent to the content site 104 (the contentprovider's server) for content. The viewer (125 a-125 n) navigates tocontent for streaming via a web browser 120. The browser may be any oneof Chrome, Safari, Firefox, Internet explorer or the like.

The content site (provider) serves up the content, which includesexecutable javascript tags. Once these tags are loaded in the viewer'scontent browser 120 (via lines 117 a, 117 b, through 117 n), they areexecuted (via lines 121 and 107) and notify the ad server 110 that thereis an impression that needs filling in the streaming content. Theimpression is then submitted to the Real-Time Bidding (RTB) marketplatform 108, where advertisers bid to fill the impression with theirvideo advertisements. The RTB market platform reads in the market floorsfor each of the competing advertisers and uses these market floors,along with the advertiser bids, to determine the winner of the auctionand their clearing price. In the event that all of the received bids aretoo low, the Auction may not clear. The operation of the RTB marketplatform 108 will be described in more detail below with reference toFIG. 2 .

Referring now to FIG. 1B, referring also to FIG. 1B, which illustratesthe architecture and flow of event data, the customer device 115 a-n mayaccess an advertiser website/app (e.g., www.com) designated by referencenumeral 126, at which point, the event and related data is generated andrecorded as “outcome event data.” The outcome event data in someembodiments of the present invention may include the “User Agent,” the“IP address,” the “Device IP,” a “Timestamp,” or an “Event Value.” Theinfrastructure or architecture of the platform 127 includes anattribution engine 128, to which the outcome event data is continuouslyprovided. In some instances, the outcome event data may be provided atdesignated intervals determined by the platform. The attribution engine128 is coupled to an optimization engine 130, which provides a biddecision and bid price to the bidder 132. As illustrated, the bidderprovides a bid or ad response to the publisher ad server 134 when a bidrequest is received by the bidder 132. Ad Exposure Event data iscontinuously tracked and recorded as each bid request is generated. Forexample, event data that may be recorded includes the “IP,” a“Timestamp,” a “Device ID,” a “Device Type,” “Content Data,” “Location,”or the like compiled at a storage location designated by referencenumeral 135. A household (“HH”) effectiveness graph 136 is coupled tothe bidder 132 and serves to provide additional data from a 3rd PartyData Enhancement server 138 as designated by signal line 146. Examplesof the additional data may include, but not limited to, postal data,latitude/longitude data, IP type, age, gender, and household income. Inaddition, new IDs are linked to known households and provided to theattribution engine 128, as designated by signal line 140. And, theattribution engine 128 adds new results to known or new households, asdesignated by signal line 142. The household effectiveness graph 136enhances bid requests with additional data as designated by signal line144. The outcome event data may be used by scoring engines to accordresponsiveness scores to advertising, which may be stored in the index.

Referring now to FIG. 2 , the RTB market platform 108 implements areal-time bidding market. In the implementations described here, the RTBmarket platform 108 conducts a market floor auction for ad placement(e.g., video), which is a specialized auction that determines an auctionwinner, auction clearing price based on the bids submitted byadvertisers, and per-advertiser market floors that are calculated anddistributed by the market floor system 100. In some implementations, anauction event store 230 may include a large collection of computersarranged in a distributed, computational, and storage grid. The auctionevent store 230 may store events from the Advertisement server 110 andRTB market platform 108. A market floor engine 220 determines andprovides market floor prices, which may in some instances be dynamicallyor selectively set by providers. In some implementations, the marketfloor engine 230 may be an analytics engine that processes auction eventdata in either real-time, near-real-time, or batch mode, determinesmarket floors based on this data, and assesses the revenue impact ofusing these market floors compared to provider “static” floors and/orother benchmarks. The provider may determine market floors by derivingdata from the CTV audience responsiveness analytics index system 224.The index system 224 may be directly coupled to either market buyerdevices 226 a, 226, or 226 n, via lines 227 a, 227 b, through 227 n, oran agency 225, via line 223, to directly provide data and revenue valueto any of these entities.

During an RBT auction, the advertisement server 110 and RTB marketplatform 108 generate a number of events that include information aboutthe context in which the RBT auction is occurring. An “event profile”(with the type of information available in the auction bids that arereceived) may be generated when all of the bids from the advertisers inan RBT auction have been received. An auction event store 230 may storeinformation available in the “auction complete” event generated when anauction has completed. The auction event store 230 may include a largecollection of computers arranged in a distributed, computational, andstorage grid. The auction event store 230 in some implementations storesevents from the advertisement server 110 and the RTB market system 108.

Referring now to FIG. 3 , an example implementation of the CTV audienceresponsiveness analytics index system 100 is illustrated. Thisimplementation of the analytics index 100 comprises data collectionengines. These engines are operated by one or more processors thatcomprise an arithmetic logic unit, a microprocessor, a general-purposecontroller or some other processor array to perform particularcomputations as programmed and provide electronic display signals to adisplay device. The processor is coupled to the bus for communicationwith the other components. The Processor processes data signals and maycomprise various computing architectures including a complex instructionset computer (CISC) architecture, a reduced instruction set computer(RISC) architecture, or an architecture implementing a combination ofinstruction sets. Although only a single processor is referenced here,multiple processors may be included. It will be obvious to one skilledin the art that other processors, operating systems, sensors, displaysand physical configurations are possible.

The processor is coupled to a memory that stores instructions and/ordata that may be executed by the processor. The memory is coupled to thebus for communication with the other components. The instructions and/ordata may comprise code for performing any and/or all of the techniquesdescribed herein. The memory may be a dynamic random access memory(DRAM) device, a static random access memory (SRAM) device, flash memoryor some other memory device known in the art.

In one embodiment, storage stores data, information and instructionsused by the ad request and delivery engines, data collector engines,optimization engines, and the direct request of source (from provider)by User/Agency etc. The storage is a non-volatile memory or similarpermanent storage device and media such as a hard disk drive, a floppydisk drive, a CD-ROM device, a DVD-ROM device, a DVD-RAM device, aDVD-RW device, a flash memory device, or some other mass storage deviceknown in the art for storing information on a more permanent basis. Thedata storage is coupled by the bus for communication with othercomponents of the analytics index system for impression evaluation andallocation.

One or more of the engines are software or routines executable on theprocessor. In some implementations, one or more of the engines storedata that, when executed by the processor, causes the collectors/modulesto perform the operations described below. In yet other implementations,one or more of the engines are instructions executable by the processorto provide the functionality described in the flow charts that follow.In still other implementations, one or more of the delivery engines arestored in the memory and are accessible and executable by the processor.

The flow chart illustrated in FIG. 3 shows the analytics index iscreated by the following steps including one or more operations forcreating and using a household (“HH”) CTV Responsiveness Index, asdescribed in block 302. This index is configured to collect data onhouseholds that are identified as “Exposed and Converting,” which datais written or stored to the operating platform'shousehold-responsiveness graph. It should be recognized that “Exposed”refers to a household that has access to connected television andcapability to view CTV/OTT advertising. The flow to create the indexflows to the next block 304 of operations, including one or moreoperation for adding increments of every instance of exposure to the“Exposed versus Outcome” index, as the “Exposed” household continues tobe exposed to future or more CTV ads. The process flows to the nextblock 310, including one or more operations for determining valuesaccording to the number, length of time from ad exposure to action, andcategory of conversions completed and assigned to the homes. The processproceeds to the next block 312, including one or more operations forcreating the household advertising responsiveness index to measurehouseholds exposed to ads, by ad category (CPG, Auto, Travel, commerce,etc.), as described by block 314. In some embodiments, as described byblock 316, the advertising responsiveness may be measured by householdsthat have either seen the CTV/OTT ad and have responded to the CTV/OTTad, usually via a “second screen response” mechanism (seeing a CTV/OTTad and responding by using their cell phone to go to the advertiserwebsite. Other examples include measuring the impact of frequency onconversions as described by block 318. For example, the response rateafter seeing one id is X; responsiveness after seeking 2 ads is Y, etc.Another example as illustrated by block 320 includes time from CTV/OTTto action. For example, how much time did it take for a house (or groupof houses) to respond to an advertisement after seeing theadvertisement. This may be measured by advertising vertical and by aprofile of the household (by a demo, etc.). As yet another exampledescribed by block 322, advertisement responsiveness by householdfrequency, including cross channel (CTV ad delivery+display+OTT+++) ismeasured and recorded in the index at the household (“HH”) level thatdictates the optimal frequency and combination of advertising formats insupport of CTV/OTT ad delivery to drive ad responsiveness.

As yet another example, described by block 324, the index provides ameasure of second-screen audience response to television advertising. Itshould be recognized that the second screen response encompassesinstances when users/viewers/audience are exposed to a CTV/OTTadvertising and then undertake one of the following actions. Theseexamples are provided for illustration purposes and are not exhaustive.The description should not be limited to these specific examples. Asecond screen response may cause a viewer to pick up a cell phone and godirectly or indirectly to the advertiser's site. Yet another example maycause a viewer to pick up a laptop computer and go directly to theCTV/OTT advertiser's site. Yet another example causes a viewer to pickup a tablet and navigate directly or indirectly to the CTV/OTTadvertiser's site. Yet another example causes viewers to go to theirdesktop computer and navigate directly or indirectly to the CTVadvertiser's site. Yet another illustrative example causes viewers topick up their cell phones and engage with a Quick Response (“QR”) codein the CTV/OTT advertising, thereby taking them to the advertiser'soffer page. Yet another example is for viewers to pick up their cellphone and dial a phone number to engage with the CTV/OTT advertiser.

In some embodiments, the application of an ad responsiveness graphserves to optimize advertising. The graph may comprise householdidentification rows (rows of “HH IDs” and columns with various valuesaccorded, including but not limited to, impressions by advertisingcategory, frequency, by device type, sequence of cross-channelimpressions, initial response rates, secondary response rates,post-conversion data (e.g., viewing to purchase action), such as averagepurchase price, order value, lifetime value etc. The graph may alsoillustrate a time decay from exposure to outcome.

Referring now to FIG. 4 , an example household graph or advertisingresponsiveness index is illustrated. The graph and index are created bya processor 402 coupled to a memory 404 with executable code execute alltasks to track and compile data and metrics for the index. Thisadvertising responsiveness graph is used to optimize advertisingdelivery to CTV and OTT streaming content. The graph 406 is an examplefor purposes of illustration. Household identifiers or identificationare recorded in rows and the columns record values for impressions. Forexample, impressions by be classified by advertising category,frequency, by device type, sequence of cross-channel impressions,initial response rates, secondary response rates, post-conversion data,such as average purchase price, order value, lifetime value. Time decayfrom exposure to outcome is another critical data point. Measures forthe Index may include frequency, time to action from first and lastexposure, frequency prior to action, sequence of device exposure,presence of other ad types in the journey, etc. Households may beassigned scores for multiple categories of advertising, for example,“10” for Gaming, “8” for Food and Beverage, and “1” for Automotive. Adcategories may include commerce, travel etc. The categories describedhere are only by way of example.

In some embodiments, measures for the index, include but are not limitedto, frequency, time to action from first to last exposure, frequencyprior to action, sequence of device exposure, presence of other types ofadvertising in the journey. Households may be accorded composite orlifetime scores, for example, some form of cumulative score accordedbased on scores and metrics tracked for multiple categories ofadvertising, for example, a “10” for gaming, a “8” for Food andBeverage, and a “1” for automotive.

In some embodiments, the household (“HH”) advertising responsivenessindex measures households exposed to advertising, by advertisingcategory (CPG, Auto, Travel, Commerce etc.). Advertising responsivenessor exposure measures households that have seen an advertisement instreaming content, on one or more of connected television (CTV/OTT),tablet, mobile phone, desktop, or laptop, responded to the CTVadvertising usually via a second screen response mechanism. Asrecognized by those skilled in the art, second screen viewing refers toseeing a CTV/OTT add and responding by using a cell phone to theadvertiser website.

Reference in the specification to “one implementation or embodiment” or“an implementation or embodiment” simply means that a particularfeature, structure, or characteristic described in connection with theimplementation or embodiment is included in at least one implementationor embodiment of the technology described. The appearances of the phrase“in one implementation or embodiment” in various places in thespecification are not necessarily all referring to the sameimplementation or embodiment.

The foregoing description of the embodiments of the present inventionhas been presented for the purposes of illustration and description. Itis not intended to be exhaustive or to limit the present invention tothe precise form disclosed. Many modifications and variations arepossible in light of the above teaching. It is intended that the scopeof the present inventive technology be limited not by this detaileddescription, but rather by the claims of this application. As will beunderstood by those familiar with the art, the present inventivetechnology may be embodied in other specific forms without departingfrom the spirit or essential characteristics thereof. Likewise, theparticular naming and division of the modules, routines, features,attributes, methodologies and other aspects are not mandatory orsignificant, and the mechanisms that implement the present inventivetechnology or its features may have different names, divisions and/orformats. Furthermore, as will be apparent to one of ordinary skill inthe relevant art, the modules, routines, features, attributes,methodologies and other aspects of the present inventive technology canbe implemented as software, hardware, firmware or any combination of thethree. Also, wherever a component, an example of which is a module, ofthe present inventive technology is implemented as software, thecomponent can be implemented as a standalone program, as part of alarger program, as a plurality of separate programs, as a statically ordynamically linked library, as a kernel loadable module, as a devicedriver, and/or in every and any other way known now or in the future tothose of ordinary skill in the art of computer programming.Additionally, the present invention is in no way limited toimplementation in any specific programming language, or for any specificoperating system or environment. Accordingly, the disclosure of thepresent inventive technology is intended to be illustrative.

What is claimed is:
 1. A method implemented by one or more processorsexecuting instructions stored in a memory for creating a household graphmeasuring exposure to advertising, the method comprising: in a computingdevice comprising the one or more processors and the memory storingexecutable code with the instructions causing the one or more processorsto execute a plurality of control actions via an interface connection,by executing one or more operations configured to: tracking, by at leastone of the one or more processors, advertising in streaming contentviewable from at least one of a connected-household-device and anover-the-top delivery mechanism, wherein the streaming content isviewable via at least one of an advertiser's website and application andvisit data of each visitor viewer is recorded, including at least one ofan initial-visit to the at least one of the advertiser's website andapplication by a viewer and an action outcome performed on the at leastone of advertiser's website and application; collect, by at least one ofthe one or more processors, signals indicative of exposure metricsrelating to the advertising, wherein the exposure metric includes acategory for the advertising; and compile, by at least one of the one ormore processors, the exposure metrics in a household graph index byhousehold identifier, wherein the household graph is an index thattracks a frequency of advertising exposure in each household; and applysaid household graph index to identify and provide additionaladvertising.
 2. The method of claim 1, wherein said exposure metricincludes the category for the advertising including at least one ofauto, travel, and commerce.
 3. The method of claim 1, wherein saidstreaming content is viewable by the at least one of the advertiser'swebsite and application and said visit data of each visitor viewer isrecorded in addition to viewer's engagement with a quick response codein advertising in the streaming content that leads to an advertiser'soffer.
 4. The method of claim 2, wherein said category tracks a type ofadvertising of interest to a particular household.
 5. The method ofclaim 4, wherein said household graph tracks a type of device used tostream said content, wherein the type of device is at least one of aconnected television, a tablet, a mobile phone, a desktop, and a laptop.6. The method of claim 5, wherein said household graph is an index thattracks a frequency of advertising exposure in each household andresponsiveness to the advertising via a second screen responsemechanism.
 7. The method of claim 3, wherein said visit data recordedincludes the action outcome performed on the at least one of theadvertiser's website and application and further determining one or morevalues according to a number, a length of time from advertisementexposure to action outcome, and a category of conversions completed andassigned to a particular household.
 8. A system, comprising: one or moreprocessors; and memory storing instructions executable by at least oneof the processors and causing the at least one of the processors to:track advertising in streaming content viewable from at least one of aconnected-household-device and an over-the-top delivery mechanism,wherein the streaming content is viewable via at least one of anadvertiser's website and application and visit data of each visitorviewer is recorded, including at least one of an initial-visit to the atleast one of the advertiser's website and application by a viewer and anaction outcome performed on the at least one of advertiser's website andapplication; collect signals indicative of exposure metrics relating tothe advertising, wherein the exposure metric includes a category for theadvertising; and compile said exposure metrics in a household graphindex by household identifier, wherein the household graph is an indexthat tracks a frequency of advertising exposure in each household; andapply said household graph index to identify and provide additionaladvertising.
 9. The system of claim 8, wherein said exposure metricincludes the category for the advertising including at least one ofauto, travel, and commerce.
 10. The system of claim 8, wherein saidstreaming content is viewable by at least one of the advertiser'swebsite and application and said visit data of each visitor viewer isrecorded in addition to viewer's engagement with a quick response codein advertising in the streaming content that leads to an advertiser'soffer.
 11. The system of claim 9, wherein said category tracks a type ofadvertising of interest to a particular household.
 12. The system ofclaim 11, wherein said household graph tracks a type of device used tostream said content, wherein the type of device is at least one of aconnected television, a tablet, a mobile phone, a desktop, and a laptop.13. The system of claim 12, wherein said household graph is an indexthat tracks the frequency of advertising exposure in each household andresponsiveness to the advertising via a second screen responsemechanism.
 14. The system of claim 10, wherein said visit data recordedincludes the action outcome performed on at least one of theadvertiser's website and application and further determining one or morevalues according to a number, a length of time from advertisementexposure to action outcome, and a category of conversions completed andassigned to a particular household.